How to Add a Column in Pandas DataFrame using Python

Introduction:

using Python.DataFrame is a common operation in data analysis, and it can be achieved using various techniques provided by the Pandas library. In this guide, we will explore the different ways to add a column to a Pandas DataFrame. Adding a new column to a DataFramePandas is one of the most widely used Python libraries for data manipulation and analysis. It provides a rich set of functions to manipulate data, and one of its powerful features is the ability to add columns to an existing

Step-by-Step Guide:

, but we will focus on the two most common methods. We will use a sample dataset to demonstrate the techniques.DataFrameThere are different techniques to add a column in Pandas

method() DataFrame.assignMethod 1: Using

The assign() with the added column. Here's an example:DataFrame. This method returns a new DataFrame method allows us to create a new column and add it to the

python

import pandas as pd # Sample dataset data = {'name': ['John', 'Jane', 'Peter', 'Mary'], 'age': [25, 30, 35, 40]} df = pd.DataFrame(data) # Adding a new column df = df.assign(city=['New York', 'Chicago', 'Los Angeles', 'Houston']) print)df(

Output:

markdown

name age city 0 John 25 New York 1 Jane 30 Chicago 2 Peter 35 Los Angeles 3 Mary 40 Houston

Method 2: Using DataFrame.insert() method

The insert() method allows us to add a new column at a specific location in the DataFrame. This method modifies the original DataFrame and returns None. Here's an example:

python

import pandas as pd # Sample dataset data = {'name': ['John', 'Jane', 'Peter', 'Mary'], 'age': [25, 30, 35, 40]} df = pd.DataFrame(data) # Adding a new column df.insert(2, 'city', ['New York', 'Chicago', 'Los Angeles', 'Houston']) print(df)

Output:

markdown

name age city 0 John 25 New York 1 Jane 30 Chicago 2 Peter 35 Los Angeles 3 Mary 40 Houston

Use Cases:

Adding a new column to a DataFrame is a common operation in data analysis. Here are some use cases:

Adding calculated columns: We can add a new column to a DataFrame by performing some calculations on existing columns. For example, we can add a new column for the sum of two existing columns, or we can apply a function to a column to create a new column.
Adding metadata: We can add metadata to a DataFrame by adding a new column. For example, we can add a column for a timestamp indicating when the data was collected, or we can add a column for a user ID to track who collected the data.

Conclusion:

Adding a column to a Pandas DataFrame is a common operation in data analysis. We have discussed two common methods to add a column to a DataFrame using the Pandas library. The assign() method allows us to create a new column and add it to the DataFrame, while the insert() method allows us to add a new column at a specific location in the DataFrame. These methods are versatile and can be used in many use cases, including adding calculated columns or metadata to a DataFrame.

We hope you found this step-by-step guide on How to Add a Column in Pandas DataFrame using Python insightful and valuable. You can learn more on JBI's Python training courses including Python for Data Analysts and Advanced Python

ABOUT THE AUTHOR

About the author: Craig Hartzel

Craig is a self-confessed geek who loves to play with and write about technology. Craig's especially interested in systems relating to e-commerce, automation, AI and Analytics.